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MultiMap: A Tool to Automatically Extract and Analyse Spatial Microscopic Data From Large Stacks of Confocal Microscopy Images

The development of 3D visualization and reconstruction methods to analyse microscopic structures at different levels of resolutions is of great importance to define brain microorganization and connectivity. MultiMap is a new tool that allows the visualization, 3D segmentation and quantification of f...

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Autores principales: Varando, Gherardo, Benavides-Piccione, Ruth, Muñoz, Alberto, Kastanauskaite, Asta, Bielza, Concha, Larrañaga, Pedro, DeFelipe, Javier
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5974206/
https://www.ncbi.nlm.nih.gov/pubmed/29875639
http://dx.doi.org/10.3389/fnana.2018.00037
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author Varando, Gherardo
Benavides-Piccione, Ruth
Muñoz, Alberto
Kastanauskaite, Asta
Bielza, Concha
Larrañaga, Pedro
DeFelipe, Javier
author_facet Varando, Gherardo
Benavides-Piccione, Ruth
Muñoz, Alberto
Kastanauskaite, Asta
Bielza, Concha
Larrañaga, Pedro
DeFelipe, Javier
author_sort Varando, Gherardo
collection PubMed
description The development of 3D visualization and reconstruction methods to analyse microscopic structures at different levels of resolutions is of great importance to define brain microorganization and connectivity. MultiMap is a new tool that allows the visualization, 3D segmentation and quantification of fluorescent structures selectively in the neuropil from large stacks of confocal microscopy images. The major contribution of this tool is the posibility to easily navigate and create regions of interest of any shape and size within a large brain area that will be automatically 3D segmented and quantified to determine the density of puncta in the neuropil. As a proof of concept, we focused on the analysis of glutamatergic and GABAergic presynaptic axon terminals in the mouse hippocampal region to demonstrate its use as a tool to provide putative excitatory and inhibitory synaptic maps. The segmentation and quantification method has been validated over expert labeled images of the mouse hippocampus and over two benchmark datasets, obtaining comparable results to the expert detections.
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spelling pubmed-59742062018-06-06 MultiMap: A Tool to Automatically Extract and Analyse Spatial Microscopic Data From Large Stacks of Confocal Microscopy Images Varando, Gherardo Benavides-Piccione, Ruth Muñoz, Alberto Kastanauskaite, Asta Bielza, Concha Larrañaga, Pedro DeFelipe, Javier Front Neuroanat Neuroscience The development of 3D visualization and reconstruction methods to analyse microscopic structures at different levels of resolutions is of great importance to define brain microorganization and connectivity. MultiMap is a new tool that allows the visualization, 3D segmentation and quantification of fluorescent structures selectively in the neuropil from large stacks of confocal microscopy images. The major contribution of this tool is the posibility to easily navigate and create regions of interest of any shape and size within a large brain area that will be automatically 3D segmented and quantified to determine the density of puncta in the neuropil. As a proof of concept, we focused on the analysis of glutamatergic and GABAergic presynaptic axon terminals in the mouse hippocampal region to demonstrate its use as a tool to provide putative excitatory and inhibitory synaptic maps. The segmentation and quantification method has been validated over expert labeled images of the mouse hippocampus and over two benchmark datasets, obtaining comparable results to the expert detections. Frontiers Media S.A. 2018-05-23 /pmc/articles/PMC5974206/ /pubmed/29875639 http://dx.doi.org/10.3389/fnana.2018.00037 Text en Copyright © 2018 Varando, Benavides-Piccione, Muñoz, Kastanauskaite, Bielza, Larrañaga and DeFelipe. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Varando, Gherardo
Benavides-Piccione, Ruth
Muñoz, Alberto
Kastanauskaite, Asta
Bielza, Concha
Larrañaga, Pedro
DeFelipe, Javier
MultiMap: A Tool to Automatically Extract and Analyse Spatial Microscopic Data From Large Stacks of Confocal Microscopy Images
title MultiMap: A Tool to Automatically Extract and Analyse Spatial Microscopic Data From Large Stacks of Confocal Microscopy Images
title_full MultiMap: A Tool to Automatically Extract and Analyse Spatial Microscopic Data From Large Stacks of Confocal Microscopy Images
title_fullStr MultiMap: A Tool to Automatically Extract and Analyse Spatial Microscopic Data From Large Stacks of Confocal Microscopy Images
title_full_unstemmed MultiMap: A Tool to Automatically Extract and Analyse Spatial Microscopic Data From Large Stacks of Confocal Microscopy Images
title_short MultiMap: A Tool to Automatically Extract and Analyse Spatial Microscopic Data From Large Stacks of Confocal Microscopy Images
title_sort multimap: a tool to automatically extract and analyse spatial microscopic data from large stacks of confocal microscopy images
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5974206/
https://www.ncbi.nlm.nih.gov/pubmed/29875639
http://dx.doi.org/10.3389/fnana.2018.00037
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